data serialize
Project description
data_serialize
This library allows reading and writing binary to string
Installation
pip3 install data_serialize
serialize and deserialize
#
import data_serialize
import numpy as np
def test_feature():
val1 = data_serialize.Int64List(value=[1, 2, 3] * 20)
val2 = data_serialize.FloatList(value=[1, 2, 3] * 20)
val3 = data_serialize.BytesList(value=[b'The china', b'boy'])
featrue = data_serialize.Features(feature=
{
"item_0": data_serialize.Feature(int64_list=val1),
"item_1": data_serialize.Feature(float_list=val2),
"item_2": data_serialize.Feature(bytes_list=val3)
}
)
example = data_serialize.Example(features=featrue)
# 序列化
serialize = example.SerializeToString()
print(serialize)
# 反序列化
example = data_serialize.Example()
example.ParseFromString(serialize)
print(example)
def test_numpyobject():
a = np.random.randint(0, 21128, size=(10,), dtype=np.int64)
b = np.random.rand(3, 4)
c = np.asarray(b'The china')
val1 = data_serialize.NumpyObject(
header='',
dtype=str(a.dtype),
shape=list(a.shape),
int64=a.reshape((-1,)).tolist(),
)
val2 = data_serialize.NumpyObject(
header='',
dtype=str(b.dtype),
shape=list(b.shape),
float64=b.reshape((-1,)).tolist(),
)
val3 = data_serialize.NumpyObject(
header='',
dtype=str(c.dtype),
shape=list(c.shape),
bytes=c.tobytes(),
)
example = data_serialize.NumpyObjectMap(numpyobjects={
"item_0": val1,
"item_1": val2,
"item_2": val3}
)
# 序列化
serialize = example.SerializeToString()
print(serialize)
# 反序列化
example = data_serialize.NumpyObjectMap()
example.ParseFromString(serialize)
print(example)
test_feature()
test_numpyobject()
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